I am working with a data set that looks like below where the year spans from 2000-2021 and the different types of energy a specific country produced (in terrawatt hours) is listed in the columns starting at "Bioenergy" going right.
# A tibble: 4,707 × 13
Country Region Conti…¹ Year Bioen…² Coal Gas Hydro Nuclear Other…³ Other…⁴ Solar Wind
<fct> <fct> <chr> <fct> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 Afghanistan Southe… Asia 2000 0 0 0 0.31 0 0.16 0 0 0
2 Albania Southe… Europe 2000 0 0 0 0.5 0 0.09 0 0 0
3 Algeria Northe… Africa 2000 0 0 22.9 0.56
# … with 4,697 more rows, and abbreviated variable names ¹Continent, ²Bioenergy, ³`Other Fossil`,
# ⁴`Other Renewables`
I ran a linear regression using the following code:
model1 <-lm(Bioenergy ~ Year*Region, data= data)
summary(model1)
and the output looks like this:
Call:
lm(formula = Bioenergy ~ Year * Region, data = data)
Residuals:
Min 1Q Median 3Q Max
-27.992 -0.988 -0.096 -0.002 141.938
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.055035 0.123232 16.676 < 2e-16 ***
Year1:Region1 1.572657 2.967886 0.530 0.596215
Year2:Region1 -0.407378 2.967886 -0.137 0.890830
Year3:Region1 0.366339 2.967886 0.123 0.901769
Year4:Region1 0.110653 2.967746 0.037 0.970259
Year5:Region1 0.117725 2.967746 0.040 0.968359
Year6:Region1 0.060654 2.967661 0.020 0.983695
Year7:Region1 0.047301 2.967661 0.016 0.987284
Year8:Region1 0.024555 2.967661 0.008 0.993399
Year9:Region1 -0.291229 2.967661 -0.098 0.921830
Year10:Region1 -0.321546 2.967661 -0.108 0.913723
Year11:Region1 -0.019364 2.967661 -0.007 0.994794
Year12:Region1 -0.031005 2.967661 -0.010 0.991665
Year13:Region1 0.145939 2.967384 0.049 0.960777
How do I get the actual value that I see in the data for "Year" and "Region" to show up in the Coefficients block such that:
"Year4:Region1" becomes
"2004:Afghanistan" (for example - I don't know if that is what it would actually be)
Thank you all!! Mark
Here is a sample of the data that can be loaded into R:
structure(list(Country = structure(c(177L, 143L, 191L, 8L, 130L,
5L, 138L, 20L, 108L, 99L, 40L, 146L, 182L, 82L, 131L, 190L, 162L,
184L, 52L, 137L, 26L, 156L, 80L, 148L, 63L, 41L, 12L, 146L, 203L,
78L, 49L, 65L, 165L, 40L, 20L, 191L, 163L, 210L, 49L, 156L, 121L,
59L, 149L, 170L, 141L, 163L, 202L, 150L, 49L, 182L, 4L, 38L,
184L, 192L, 109L, 37L, 13L, 212L, 194L, 123L, 77L, 118L, 59L,
113L, 34L, 158L, 37L, 215L, 17L, 87L, 60L, 133L, 195L, 15L, 147L,
127L, 45L, 43L, 205L, 3L, 93L, 114L, 106L, 175L, 127L, 100L,
119L, 105L, 211L, 202L, 39L, 203L, 110L, 190L, 58L, 21L, 207L,
4L, 13L, 154L, 44L, 88L, 198L, 62L, 129L, 171L, 67L, 179L, 20L,
159L, 212L, 154L, 80L, 148L, 212L, 107L, 5L, 53L, 9L, 159L, 76L,
209L, 116L, 182L, 183L, 56L, 108L, 79L, 173L, 215L, 139L, 117L,
88L, 138L, 67L, 29L, 189L, 80L, 188L, 156L, 167L, 29L, 123L,
98L, 95L, 63L, 111L, 155L, 36L, 55L, 4L, 193L, 215L, 158L, 60L,
113L, 202L, 85L, 22L, 46L, 50L, 17L, 145L, 152L, 5L, 119L, 169L,
172L, 156L, 131L, 36L, 162L, 151L, 125L, 6L, 34L, 196L, 154L,
42L, 137L, 126L, 166L, 107L, 131L, 29L, 145L, 129L, 76L, 20L,
35L, 53L, 197L, 129L, 197L, 145L, 123L, 141L, 211L, 191L, 112L,
123L, 201L, 214L, 103L, 118L, 42L, 182L, 40L, 196L, 174L, 85L,
22L, 77L, 2L, 200L, 140L, 81L, 152L, 173L, 22L, 125L, 143L, 175L,
125L, 212L, 95L, 115L, 107L, 66L, 64L, 128L, 194L, 193L, 85L,
103L, 15L, 124L, 98L, 156L, 144L, 41L, 98L, 123L, 214L, 127L,
111L, 51L, 25L, 105L, 108L), levels = c("Afghanistan", "Albania",
"Algeria", "American Samoa", "Angola", "Antigua and Barbuda",
"Argentina", "Armenia", "Aruba", "Australia", "Austria", "Azerbaijan",
"Bahamas (the)", "Bahrain", "Bangladesh", "Barbados", "Belarus",
"Belgium", "Belize", "Benin", "Bermuda", "Bhutan", "Bolivia",
"Bosnia Herzegovina", "Botswana", "Brazil", "Brunei Darussalam",
"Bulgaria", "Burkina Faso", "Burundi", "Cabo Verde", "Cambodia",
"Cameroon", "Canada", "Cayman Islands (the)", "Central African Republic (the)",
"Chad", "Chile", "China", "Colombia", "Comoros (the)", "Congo (the Democratic Republic of the)",
"Congo (the)", "Cook Islands (the)", "Costa Rica", "Cote d'Ivoire",
"Croatia", "Cuba", "Cyprus", "Czechia", "Denmark", "Djibouti",
"Dominica", "Dominican Republic (the)", "Ecuador", "Egypt", "El Salvador",
"Equatorial Guinea", "Eritrea", "Estonia", "Eswatini", "Ethiopia",
"Falkland Islands (the) [Malvinas]", "Faroe Islands (the)", "Fiji",
"Finland", "France", "French Guiana", "French Polynesia", "Gabon",
"Gambia (the)", "Georgia", "Germany", "Ghana", "Gibraltar", "Greece",
"Greenland", "Grenada", "Guadeloupe", "Guam", "Guatemala", "Guinea",
"Guinea-Bissau", "Guyana", "Haiti", "Honduras", "Hong Kong",
"Hungary", "Iceland", "India", "Indonesia", "Iran (Islamic Republic of)",
"Iraq", "Ireland", "Israel", "Italy", "Jamaica", "Japan", "Jordan",
"Kazakhstan", "Kenya", "Kiribati", "Korea (the Democratic People's Republic of)",
"Kosovo", "Kuwait", "Kyrgyzstan", "Lao People's Democratic Republic (the)",
"Latvia", "Lebanon", "Lesotho", "Liberia", "Libya", "Lithuania",
"Luxembourg", "Macao", "Madagascar", "Malawi", "Malaysia", "Maldives",
"Mali", "Malta", "Martinique", "Mauritania", "Mauritius", "Mexico",
"Moldova", "Mongolia", "Montenegro", "Montserrat", "Morocco",
"Mozambique", "Myanmar", "Namibia", "Nauru", "Nepal", "Netherlands",
"New Caledonia", "New Zealand", "Nicaragua", "Niger (the)", "Nigeria",
"Niue", "North Macedonia", "Norway", "Oman", "Pakistan", "Palestine, State of",
"Panama", "Papua New Guinea", "Paraguay", "Peru", "Philippines (the)",
"Poland", "Portugal", "Puerto Rico", "Qatar", "Reunion", "Romania",
"Russian Federation (the)", "Rwanda", "Saint Helena, Ascension and Tristan da Cunha",
"Saint Kitts and Nevis", "Saint Lucia", "Saint Pierre and Miquelon",
"Saint Vincent and the Grenadines", "Samoa", "Sao Tome and Principe",
"Saudi Arabia", "Senegal", "Serbia", "Seychelles", "Sierra Leone",
"Singapore", "Slovakia", "Slovenia", "Solomon Islands", "Somalia",
"South Africa", "South Korea", "South Sudan", "Spain", "Sri Lanka",
"Sudan (the)", "Suriname", "Sweden", "Switzerland", "Syrian Arab Republic (the)",
"Taiwan", "Tajikistan", "Tanzania, the United Republic of", "Thailand",
"Timor-Leste", "Togo", "Tonga", "Trinidad and Tobago", "Tunisia",
"Turkey", "Turkmenistan", "Turks and Caicos Islands (the)", "Uganda",
"Ukraine", "United Arab Emirates", "United Kingdom", "United States of America",
"Uruguay", "Uzbekistan", "Vanuatu", "Venezuela (Bolivarian Republic of)",
"Viet Nam", "Virgin Islands (British)", "Virgin Islands (U.S.)",
"Western Sahara", "Yemen", "Zambia", "Zimbabwe"), class = "factor"),
Region = structure(c(5L, 19L, 16L, 21L, 11L, 10L, 2L, 20L,
12L, 21L, 14L, 15L, 15L, 20L, 5L, 5L, 3L, 14L, 5L, 8L, 14L,
21L, 9L, 4L, 14L, 5L, 21L, 15L, 12L, 3L, 21L, 8L, 3L, 14L,
20L, 16L, 3L, 3L, 21L, 21L, 19L, 5L, 8L, 19L, 20L, 3L, 21L,
14L, 21L, 15L, 13L, 14L, 14L, 16L, 21L, 10L, 3L, 11L, 13L,
20L, 1L, 16L, 5L, 12L, 1L, 7L, 10L, 5L, 7L, 6L, 12L, 17L,
3L, 18L, 21L, 6L, 4L, 10L, 14L, 11L, 21L, 22L, 15L, 19L,
6L, 15L, 15L, 21L, 3L, 21L, 6L, 12L, 17L, 5L, 10L, 1L, 8L,
13L, 3L, 19L, 13L, 7L, 15L, 5L, 3L, 5L, 22L, 6L, 20L, 7L,
11L, 19L, 9L, 4L, 11L, 16L, 10L, 3L, 3L, 7L, 19L, 16L, 5L,
15L, 11L, 11L, 12L, 3L, 16L, 5L, 4L, 5L, 7L, 2L, 22L, 20L,
15L, 9L, 6L, 21L, 10L, 20L, 20L, 6L, 21L, 14L, 20L, 3L, 10L,
14L, 13L, 20L, 5L, 7L, 12L, 12L, 21L, 3L, 18L, 20L, 7L, 7L,
21L, 16L, 10L, 15L, 20L, 20L, 21L, 5L, 10L, 3L, 14L, 4L,
3L, 1L, 11L, 19L, 10L, 8L, 7L, 13L, 16L, 5L, 20L, 21L, 3L,
19L, 20L, 3L, 3L, 21L, 3L, 21L, 21L, 20L, 20L, 3L, 16L, 11L,
20L, 7L, 5L, 6L, 16L, 10L, 15L, 14L, 11L, 7L, 3L, 18L, 1L,
19L, 5L, 20L, 4L, 16L, 16L, 18L, 4L, 19L, 19L, 4L, 11L, 21L,
6L, 16L, 12L, 12L, 19L, 13L, 20L, 3L, 6L, 18L, 5L, 6L, 21L,
12L, 5L, 6L, 20L, 5L, 6L, 20L, 12L, 17L, 21L, 12L), levels = c("Northern America",
"Austrailia & New Zealand", "Carribbean", "Central America",
"Eastern Africa", "Eastern Asia", "Eastern Europe", "Melanesia",
"Micronesia", "Middle Africa", "Northern Africa", "Northern Europe",
"Polynesia", "South America", "South Central Asia", "Southeastern Asia",
"Southern Africa", "Southern Asia", "Southern Europe", "Western Africa",
"Western Asia", "Western Europe"), class = "factor"), Continent = c("Africa",
"Europe", "Asia", "Asia", "Africa", "Africa", "Oceania",
"Africa", "Europe", "Asia", "South America", "Asia", "Asia",
"Africa", "Africa", "Africa", "North America", "South America",
"Africa", "Oceania", "South America", "Asia", "Oceania",
"North America", "South America", "Africa", "Asia", "Asia",
"Europe", "North America", "Europe", "Oceania", "North America",
"South America", "Africa", "Asia", "North America", "North America",
"Europe", "Asia", "Europe", "Africa", "Oceania", "Europe",
"Africa", "North America", "Asia", "South America", "Europe",
"Asia", "Oceania", "South America", "South America", "Asia",
"Asia", "Africa", "North America", "Africa", "Oceania", "Africa",
"North America", "Asia", "Africa", "Europe", "North America",
"Europe", "Africa", "Africa", "Europe", "Asia", "Europe",
"Africa", "North America", "Asia", "Asia", "Asia", "North America",
"Africa", "South America", "Africa", "Asia", "Europe", "Asia",
"Europe", "Asia", "Asia", "Asia", "Asia", "North America",
"Asia", "Asia", "Europe", "Africa", "Africa", "Africa", "North America",
"Oceania", "Oceania", "North America", "Europe", "Oceania",
"Europe", "Asia", "Africa", "North America", "Africa", "Europe",
"Asia", "Africa", "Europe", "Africa", "Europe", "Oceania",
"North America", "Africa", "Asia", "Africa", "North America",
"South America", "Europe", "Europe", "Asia", "Africa", "Asia",
"Africa", "Africa", "Europe", "North America", "Asia", "Africa",
"North America", "Africa", "Europe", "Oceania", "Europe",
"Africa", "Asia", "Oceania", "Asia", "Asia", "Africa", "Africa",
"Africa", "Asia", "Asia", "South America", "Africa", "North America",
"Africa", "South America", "Oceania", "Africa", "Africa",
"Europe", "Europe", "Europe", "Asia", "North America", "Asia",
"Africa", "Europe", "Europe", "Asia", "Asia", "Africa", "Asia",
"Africa", "Africa", "Asia", "Africa", "Africa", "North America",
"South America", "North America", "North America", "North America",
"Africa", "Europe", "Africa", "Oceania", "Europe", "Oceania",
"Asia", "Africa", "Africa", "Asia", "North America", "Europe",
"Africa", "North America", "North America", "Asia", "North America",
"Asia", "Asia", "Africa", "Africa", "North America", "Asia",
"Africa", "Africa", "Europe", "Africa", "Asia", "Asia", "Africa",
"Asia", "South America", "Africa", "Europe", "North America",
"Asia", "North America", "Europe", "Africa", "Africa", "North America",
"Asia", "Asia", "Asia", "North America", "Europe", "Europe",
"North America", "Africa", "Asia", "Asia", "Asia", "Europe",
"Europe", "Europe", "Oceania", "Africa", "North America",
"Asia", "Asia", "Africa", "Asia", "Asia", "Europe", "Africa",
"Asia", "Africa", "Africa", "Asia", "Africa", "Europe", "Africa",
"Asia", "Europe"), Year = structure(c(17L, 10L, 20L, 8L,
6L, 6L, 8L, 12L, 7L, 8L, 22L, 1L, 8L, 5L, 19L, 15L, 1L, 16L,
11L, 4L, 19L, 18L, 9L, 5L, 1L, 5L, 18L, 3L, 14L, 10L, 21L,
9L, 9L, 7L, 8L, 18L, 18L, 6L, 3L, 8L, 20L, 7L, 7L, 2L, 9L,
15L, 6L, 19L, 22L, 11L, 12L, 13L, 7L, 17L, 12L, 12L, 6L,
10L, 12L, 1L, 11L, 9L, 3L, 5L, 13L, 3L, 1L, 13L, 5L, 20L,
4L, 4L, 10L, 11L, 9L, 6L, 19L, 4L, 17L, 12L, 15L, 4L, 14L,
19L, 4L, 19L, 10L, 21L, 6L, 5L, 16L, 16L, 10L, 19L, 14L,
12L, 2L, 1L, 2L, 11L, 5L, 20L, 15L, 2L, 12L, 13L, 1L, 8L,
7L, 13L, 3L, 17L, 13L, 14L, 7L, 9L, 1L, 17L, 7L, 19L, 22L,
11L, 13L, 4L, 19L, 4L, 6L, 2L, 2L, 16L, 6L, 4L, 13L, 3L,
20L, 12L, 22L, 22L, 19L, 21L, 2L, 11L, 5L, 5L, 20L, 17L,
19L, 11L, 18L, 20L, 21L, 12L, 2L, 11L, 11L, 13L, 19L, 13L,
21L, 8L, 10L, 8L, 12L, 7L, 10L, 4L, 5L, 13L, 15L, 14L, 14L,
17L, 9L, 16L, 22L, 17L, 21L, 6L, 13L, 6L, 2L, 6L, 18L, 9L,
3L, 14L, 20L, 15L, 9L, 22L, 13L, 4L, 15L, 14L, 8L, 12L, 13L,
12L, 7L, 16L, 4L, 11L, 20L, 3L, 7L, 9L, 9L, 4L, 22L, 22L,
2L, 14L, 17L, 7L, 10L, 15L, 16L, 6L, 8L, 22L, 5L, 3L, 11L,
18L, 19L, 5L, 19L, 15L, 8L, 8L, 19L, 10L, 2L, 8L, 4L, 17L,
20L, 12L, 7L, 11L, 19L, 15L, 16L, 5L, 18L, 20L, 4L, 1L, 12L,
12L), levels = c("2000", "2001", "2002", "2003", "2004",
"2005", "2006", "2007", "2008", "2009", "2010", "2011", "2012",
"2013", "2014", "2015", "2016", "2017", "2018", "2019", "2020",
"2021"), class = "factor"), Bioenergy = c(0, 0, 12.19, 0,
0, 0, 0.7, 0, 0.04, 0.02, 1.24, 0.77, 0.01, 0, 0.11, 0.57,
0, 0.01, 0, 0, 51.76, 0.03, 0, 0.03, 0, 0, 0, 0.82, 18.1,
0, 0.06, 0.1, 0, 0.2, 0, 9.05, 0, 0, 0, 0, 0.01, 0, 0.1,
0, 0.01, 0, 0, 0, 0.06, 0.04, 0, 0, 0, 0, 0, 0.01, 0, 0,
0, 0, 0, 0.8, 0, 0.01, 10.02, 0, 0.01, 0.34, 0, 0, 0.03,
0, 0, 0.01, 0, 0, 0.04, 0.02, 1.51, 0, 0, 0.03, 0, 0.26,
0, 0, 0, 0, 0, 0, 54.07, 28.47, 0, 0.56, 0, 0, 0, 0, 0, 2.61,
0, 2.23, 0, 0.01, 0, 0, 2.48, 0.36, 0, 0.47, 0, 3.07, 0,
0.1, 0, 0, 0, 0, 0, 0.48, 0.45, 0.06, 0, 0, 0.91, 0, 0.04,
0.39, 0, 0.42, 0.49, 0.07, 1.65, 0.55, 8.64, 0, 0, 0, 1.98,
0.03, 0, 0, 0, 15.75, 0.1, 0, 0, 0, 0, 1.6, 0, 0, 0.28, 0.11,
0.74, 0.22, 0.01, 0, 0, 0, 1.85, 0.03, 0, 0.03, 0, 0, 0.06,
0, 0.03, 0.17, 0, 0, 0.11, 7.12, 0, 10.63, 0, 1.68, 0, 0,
0, 0.01, 0.21, 0.03, 0, 0, 0, 0.22, 0, 0, 0, 0.08, 0, 0.88,
0, 0, 0.02, 0, 1.87, 0, 0, 0.19, 0.17, 0, 0.62, 0, 0.06,
0.16, 0, 1.66, 0, 0, 0, 0, 0.09, 0, 2.44, 0.03, 0, 0, 6.63,
0, 0.22, 7.51, 0, 0, 0, 0.01, 9.95, 0, 0, 0, 0, 0, 0, 0.03,
0.36, 20.06, 0, 0.35, 0, 22.86, 0, 0.01, 0, 0, 2.49, 0, 0,
0.12), Coal = c(0, 5.3, 34.7, 0, 11.12, 0, 5.85, 0, 0, 0,
6.21, 0.53, 0, 0, 0, 0, 0, 0, 0, 0, 22.52, 0, 0, 0, 0, 0,
0, 0.55, 130.26, 0, 0, 0, 0, 2.23, 0, 34.81, 0, 0, 0, 0,
0, 0, 0, 21.86, 0.66, 0, 0, 0, 0, 0, 0, 26.34, 0, 0, 0, 0,
0, 0, 0, 0, 0, 31.03, 0, 0, 61.98, 20.31, 0, 3.22, 0, 22.55,
0, 0.01, 0, 1.75, 0, 3.3, 0, 0, 0, 0, 0, 0, 0.81, 4.62, 3.02,
74.83, 0, 0, 0, 0, 4046.17, 75.88, 0, 0, 0, 0, 0, 0, 0, 7.1,
0, 4.03, 0, 0, 0, 0, 27, 160.9, 0, 159.39, 0, 12.63, 0, 0.4,
0, 0, 0, 0, 0, 167.77, 6.2, 15.91, 0.23, 0, 0, 0, 0, 0.82,
0, 3.98, 0, 0, 6.34, 5.9, 3.64, 0, 0.55, 0, 132.26, 0, 0,
0, 0, 254, 19.14, 0, 0, 0, 0, 0, 0, 0, 4.33, 20.68, 0, 0,
0, 0, 0, 0, 45.94, 0, 0, 14.07, 0, 0, 0, 0, 0, 0, 0, 0, 0.38,
31.48, 0, 58.29, 0, 15.23, 0, 0, 3.07, 0, 10.08, 0, 0, 0,
0, 25.75, 0, 0, 0, 31.42, 0, 61.92, 0, 0, 0.77, 0, 23.04,
0, 0, 67.3, 1.3, 8.61, 26.63, 0, 0, 2.09, 0, 2.11, 0, 0,
0, 0, 0, 0, 1.81, 14.26, 0, 0, 21.74, 5.12, 5.29, 28.54,
0, 25.9, 0, 0, 13.89, 0, 1.55, 0, 0, 0, 8.72, 1.66, 0.78,
267.62, 0, 0.04, 0, 341.57, 0, 0, 5.27, 0, 25.31, 0.89, 0,
0), Gas = c(0, 0, 118.02, 1.4, 2.44, 0, 8.19, 0, 2.1, 9.73,
14.37, 29.66, 0, 0, 1.95, 0, 0, 0, 0, 0, 51.99, 42.79, 0,
0, 0, 0, 13.49, 31.58, 95.84, 0, 0, 0, 0, 7.41, 0, 117.91,
0, 0, 0, 18.29, 1.83, 0, 0, 0.5, 13.81, 0, 57.05, 0, 0, 0,
0, 12.48, 0, 0, 6.58, 0, 0, 0, 0, 0, 0, 71.48, 0, 2.69, 56.52,
8.97, 0, 0, 29.31, 12.16, 0.5, 0, 6.96, 21.34, 0.2, 0, 0,
0, 1.06, 46.44, 45.09, 2.62, 0, 0.48, 0, 21.47, 0, 66.89,
0, 49.27, 166.91, 99.88, 0, 1.92, 0, 0, 0, 0, 0, 14.9, 0,
8.7, 12.42, 0, 0, 0, 11.51, 79.62, 0, 495.72, 0, 12.58, 0,
0, 0, 0, 0, 0, 0, 497.51, 22.3, 44.77, 0, 0, 1.71, 62.61,
1.49, 0, 17.72, 0, 0, 0, 9.4, 5.59, 39.31, 0, 0.27, 0, 93.11,
44.48, 0, 0, 0, 221.73, 45.43, 0, 0, 0, 0, 1.38, 0, 0, 0,
7.26, 0.3, 2.88, 126.61, 0, 0, 3.5, 0.98, 29.81, 20.56, 9.57,
0, 0, 0, 0, 36.34, 0, 0, 0, 7.72, 173.69, 0, 59.59, 18.73,
13.61, 0, 0, 2.21, 0, 0, 0, 0, 24.67, 0, 6.79, 0, 0, 0, 63.54,
0, 105.12, 13.32, 0, 20.89, 0, 88.93, 34.03, 0, 15.7, 0,
0, 67.39, 0, 0, 6.95, 19.08, 4.19, 0, 0, 0, 0, 0, 0, 0, 10.39,
26.65, 0, 84.38, 0, 0.55, 178.21, 0, 18.5, 0.66, 0, 10.56,
0, 0, 0, 0, 0, 0, 44.93, 0, 356.58, 16.06, 4.8, 0, 433.09,
0, 0, 0, 0, 9.76, 0, 54.04, 3.01), Hydro = c(0, 0.68, 0,
0.13, 7.34, 0, 0, 1.99, 0, 19.64, 58.94, 32.51, 5.44, 0.33,
6.34, 0, 1.83, 0.16, 8.17, 0.08, 0, 0, 0.59, 1.5, 0.15, 0,
0.01, 381.73, 0.09, 18.63, 0, 2.91, 0.13, 0.01, 0.17, 3.46,
0, 0.43, 6.97, 0, 0, 0.23, 0.49, 0.39, 0, 135.47, 0.05, 8.34,
82.83, 12.66, 19.2, 0, 57.6, 0.03, 0, 0.62, 0, 0.18, 0.68,
0, 3.39, 0, 8.95, 0, 0, 0, 4.72, 0, 45.94, 1.7, 1.83, 0,
0.06, 83.16, 0.25, 7, 1.19, 0, 0.06, 19.33, 6.31, 0, 3.29,
0.99, 0, 26.41, 2.9, 10.14, 0.58, 0.05, 7.18, 0, 5.94, 66.43,
0.84, 1.86, 0.08, 0.63, 37.1, 0, 0, 2.56, 30.55, 0, 0.52,
27.38, 0, 4, 0, 0.12, 0.13, 0, 0, 0, 0, 0, 0.56, 174.07,
0, 0.74, 65.07, 8.36, 0, 22.5, 60.12, 0.03, 1.6, 0, 0.31,
0, 10.93, 0, 0, 424.05, 16.83, 0.33, 12.37, 51.98, 65.85,
5.89, 0.32, 0.05, 6.42, 0, 2.35, 173.51, 30.51, 0, 0, 16.17,
0.05, 0.7, 0, 0, 9.27, 0, 38.29, 0, 57.86, 0.89, 131.7, 0.22,
0.12, 0.5, 0.23, 0, 7.04, 30.09, 133.66, 1.39, 0, 0, 0.15,
8.58, 6.59, 15.97, 8.58, 12.8, 0, 11.02, 0, 12.77, 0, 0,
0, 0, 0, 0, 0, 0, 0, 21.81, 0.76, 0.1, 0, 0.42, 0.2, 1.34,
63.77, 6.96, 0, 3.21, 0.05, 6.72, 0.09, 0, 2.32, 0, 3.79,
8.02, 0, 2.75, 0.04, 0, 0.16, 1.58, 55.19, 12.52, 6.35, 0,
6.53, 375.97, 0, 0.02, 29.91, 1.07, 2.67, 0, 0, 0, 5.91,
0.11, 0.18, 8.19, 387.87, 0.54, 0, 0, 10.78, 0.1, 0.94, 5.66,
9.92, 0, 0.02, 3.71, 0.04, 3.51, 0, 0), Nuclear = c(0, 0,
0, 0, 0, 0, 0, 0, 0, 163.05, 0, 5.73, 0, 0, 0, 0, 2.35, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 15.16, 4.08, 0, 0, 0, 0, 0, 0,
5.88, 0, 0, 0, 0, 0, 0, 0, 48.23, 0, 0, 0, 0, 0, 0, 0, 0,
439.73, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 12.75, 0, 0, 0, 0, 0, 0, 0, 0, 52.76, 0,
92.54, 0, 0, 0, 0, 0, 60.47, 0, 0, 0, 0, 0, 0, 0, 0, 2.41,
0, 0, 10.32, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 137.47, 0,
0, 0, 0, 0, 0, 77.49, 0, 0, 0, 47.94, 0, 0, 0, 0, 14.8, 0,
0, 0, 0, 52.17, 63.75, 47.31, 0, 0, 0, 0, 169.07, 58.3, 0,
0, 0, 0, 0, 0, 0, 0, 0, 25.47, 0, 0, 0, 32.22, 0, 0, 0, 15.43,
0, 0, 10.4, 0, 0, 0, 0, 0, 0, 0, 7.71, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4.25, 0, 9.83, 0, 0, 436.48,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 14.97, 0, 0, 25.56, 0, 0, 0, 0, 0, 0, 0, 0, 0, 97.58,
0, 0, 0, 22.3, 0, 14.28, 0, 0, 0, 0, 0, 0, 0, 0, 0), `Other Fossil` = c(0.05,
2.68, 0.44, 0.39, 3.98, 4.75, 0, 0, 0.01, 24.45, 0, 19.49,
4.77, 0.06, 4.39, 0, 0, 20.76, 7.15, 0.02, 0.31, 2.06, 0.4,
0, 1.33, 0.04, 0.02, 9.39, 5.79, 18.85, 6.68, 3.61, 0.81,
10.32, 0.38, 0.05, 1.58, 0.98, 0, 0, 0, 0.04, 0.4, 3.71,
1, 0.74, 0.46, 2.62, 0, 0.12, 0, 0.15, 11.74, 0.11, 1.22,
6.78, 4.63, 2.9, 0.5, 0.31, 2.07, 0.08, 0, 0.03, 0.1, 0.37,
0, 0, 0.52, 3.44, 0.26, 0.67, 4.83, 117.52, 0.26, 3.74, 0.13,
0.38, 0.05, 0, 0, 0.45, 0.24, 0.89, 0.62, 21.03, 15.85, 2.62,
0.96, 14.61, 2.45, 0, 13.47, 3.48, 3.76, 0, 0.35, 0.31, 3.41,
0, 0.05, 2.87, 18.18, 1.89, 0.23, 67.68, 0.16, 5.86, 0.41,
1.62, 1.49, 0.38, 2.05, 0.03, 0, 0.03, 0.33, 22.53, 0.28,
0.69, 1.75, 0, 0, 0.98, 4.23, 0.82, 5.48, 0.04, 3.35, 0,
7.06, 0.39, 2.11, 13.6, 0.09, 5.07, 0.66, 1.24, 2.55, 5.81,
4.92, 2.43, 0.07, 0.02, 2.34, 10.1, 12.38, 0, 74.67, 0.1,
0, 0.62, 0.14, 0, 1.24, 0, 2.72, 2.3, 3.34, 1.26, 9.35, 0.42,
0.04, 0.36, 0.83, 0.55, 1.85, 48.8, 0.2, 0.03, 0.02, 0.05,
0.3, 17.56, 1.14, 1.3, 0.92, 14.87, 0.26, 5.46, 1.01, 20.85,
0.26, 0.61, 0, 0.03, 0, 0.5, 0, 0.05, 0.61, 3.07, 0.21, 5.33,
0, 0.42, 1.36, 0.16, 11.26, 8.88, 0.59, 0.34, 0, 0.11, 0.16,
1.76, 4.29, 0.34, 0, 0.08, 0.03, 0, 0.12, 0.24, 5.31, 0.11,
0, 10.25, 5.48, 0.04, 0.53, 13.94, 0, 0.06, 3.34, 0.28, 4.12,
0, 0.29, 0.26, 3.62, 4.75, 0.04, 0, 5.95, 1.9, 0, 1.26, 8.26,
0.02, 0, 0, 16.1, 4.38, 0.04, 0.86, 0.86, 0.23, 0.96, 1.23
), `Other Renewables` = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 13.06,
0, 0.28, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0.47, 0, 0, 0, 0, 0, 0, 0, 1.45, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 2.34, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 7.3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.4, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1.21, 0, 0, 0.46, 0.03, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0.9, 0, 0, 0, 0, 0, 0, 0, 0, 6.68, 0, 0, 0, 0, 0,
11.04, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.1, 0,
0, 0.06, 0, 0, 0, 0, 0, 0, 0.56, 10.24, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1.22, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.01, 0, 0, 0, 0, 0, 0, 0,
9.6, 0, 0, 0, 0, 0, 0, 0), Solar = c(0, 0.01, 0, 0, 0, 0.01,
0, 0, 0, 1.28, 0, 0.01, 4.88, 0, 0.12, 0, 0, 0, 0, 0, 0,
0.04, 0, 0, 0.68, 0, 0, 6.59, 1.11, 0.03, 0, 0, 0, 0.03,
0.03, 0, 0.72, 0, 0, 0, 0, 0, 0.01, 0.01, 0.02, 0, 0, 0.01,
0, 0, 0.04, 0, 0.02, 0, 0.01, 0, 0.22, 0.05, 0, 0, 0.02,
0, 0, 0, 0, 0, 0, 0, 0.01, 0.01, 0, 0.02, 0, 22.95, 0, 0,
0.02, 0.01, 0, 0.04, 0, 0, 0, 0.01, 0, 6.06, 0.06, 0, 0,
0.03, 0.16, 0, 0, 0.01, 0, 0, 0, 0, 0.02, 0, 0, 0.01, 0,
0, 0.05, 0.01, 0, 4.43, 0.03, 0.03, 0.03, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0.01, 0, 0, 0, 0, 0, 0, 0, 0.56, 0.01, 0, 0,
0, 0, 0, 0, 0, 4.9, 0.01, 4.05, 0, 0, 0, 0, 0.09, 0.16, 20.67,
0, 0, 0, 0.11, 0, 0, 0, 0.05, 0, 0.01, 0, 0, 0, 0.83, 0.01,
0.02, 0.02, 0, 0, 0, 0.01, 0, 0, 0, 0, 0, 0.14, 0, 0, 0,
0, 0, 0, 0, 1.52, 0, 0, 0, 0, 0, 0, 0, 0.01, 0, 3.9, 0, 0.04,
0, 0, 0.14, 0, 6.39, 0, 0, 0, 0, 0.05, 0, 0, 0.42, 0.01,
0, 0, 0, 0, 0, 0, 0, 0.01, 0, 0, 3.65, 0, 0, 0.08, 0.02,
0, 0.17, 0, 0.01, 0, 0, 0, 0.02, 0, 0, 0, 1.48, 0.08, 0,
0, 0, 0, 0.02, 0.02, 0, 0, 0, 2.38, 0, 0, 0.01, 0.01), Wind = c(0,
6.15, 0, 0, 0, 0.11, 0, 0.14, 0.01, 27.77, 0, 1.01, 10.87,
0, 0.32, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.01, 0, 0, 55.43, 7.55,
0, 0, 0, 0, 0.64, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.49, 0, 2.22,
0, 0, 0, 0, 0, 0, 4.07, 0, 0, 0, 0.24, 0.3, 0, 0, 0.02, 0,
0, 0, 0, 0, 0, 0, 0.05, 0, 0, 0, 0, 5.22, 0, 0, 0.02, 0.08,
0, 0, 0, 0, 0, 0, 0, 38.12, 0, 0.05, 0, 0.02, 0.49, 0, 0,
6.11, 0.19, 0.15, 0, 0, 1.33, 0, 0, 0, 0, 0, 0.6, 0.02, 0,
7.27, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.01, 0, 0, 0.2, 0, 0, 0,
0.86, 0, 0, 0, 1.29, 0, 0.06, 0, 0, 2.7, 0, 0, 0, 0.72, 2.49,
31.96, 0.14, 0, 0.26, 0, 0, 0, 56.44, 0, 0, 0, 0.47, 0, 0,
0, 0.13, 0, 0, 0, 5.86, 0, 23.95, 0, 0.06, 0, 0.33, 0, 0.01,
0.06, 0.89, 0, 0, 0, 0, 0.75, 0, 0, 0.07, 0.62, 0, 0, 0,
3.02, 0, 0, 0, 0, 0, 0, 0.05, 0, 0, 3.55, 0, 4.58, 0, 0.11,
0.12, 0, 17.32, 0, 0, 0, 0.11, 0.26, 0.01, 0, 0.67, 0.08,
0, 0, 0, 0, 0, 0, 0.05, 0, 0, 0.52, 4.14, 0, 0.27, 33.24,
0.04, 0, 0.07, 0, 0, 0, 0, 0, 0.34, 0, 0, 0, 17.78, 0.02,
0, 0, 0.06, 0, 0.01, 0, 0.07, 0, 0, 0.33, 0, 0, 0, 0)), row.names = c(NA,
-250L), class = c("tbl_df", "tbl", "data.frame"))
CodePudding user response：
model1$xlevels gives the variables and levels for the predictors for model1. names gives the variable names. With the summary as a dataframe, you can replace those variable names within the terms column of the summary.
library(tidyverse)
# Summary ast tibble, with terms as column
broom::tidy(model1) %>%
mutate(term = stringr::str_replace_all(term,
# Get variable names
model1$xlevels %>% names() %>%
# Collapse, separated by "|" to replace any occurrences
str_c(., collapse = "|"),
"") # Replace with blank
)